TSIEX10

Study Treatment Compliance

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# Program Name:              tsiex10.R

# Prep Environment

library(envsetup)
library(tern)
library(dplyr)
library(rtables)
library(junco)

# Define script level parameters:

# - Define output ID and file location

tblid <- "TSIEX10"
fileid <- tblid
tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid)
string_map <- default_str_map


trtvar <- "TRT01A"
popfl <- "SAFFL"

catlevels <- c("<60%", "60% to <80%", "80% to <100%", ">=100%")

combined_colspan_trt <- TRUE

if (combined_colspan_trt == TRUE) {
  # Set up levels and label for the required combined columns
  add_combo <- add_combo_facet(
    "Combined",
    label = "Combined",
    levels = c("Xanomeline High Dose", "Xanomeline Low Dose")
  )

  # choose if any facets need to be removed - e.g remove the combined column for placebo
  rm_combo_from_placebo <- cond_rm_facets(
    facets = "Combined",
    ancestor_pos = NA,
    value = " ",
    split = "colspan_trt"
  )

  mysplit <- make_split_fun(post = list(add_combo, rm_combo_from_placebo))
}

# Process Data:

# Read in required data
adsl <- pharmaverseadamjnj::adsl %>%
  filter(!!rlang::sym(popfl) == "Y") %>%
  select(STUDYID, USUBJID, all_of(trtvar), all_of(popfl))

# If AVISIT is not present in ADEXSUM than create 'Overall' as the Visit, which is used
# for the filtering AVISIT records if it does exist
adexsum <- pharmaverseadamjnj::adexsum %>%
  mutate(VISIT = if (exists("AVISIT")) AVISIT else "Overall") %>%
  filter(PARAMCD == "TRTCOMP" & !is.na(AVAL) & VISIT == "Overall") %>%
  select(USUBJID, PARAMCD, AVAL, AVALCAT1)

adsl$colspan_trt <- factor(
  ifelse(adsl[[trtvar]] == "Placebo", " ", "Active Study Agent"),
  levels = c("Active Study Agent", " ")
)

# join data together
ex <- adexsum %>% inner_join(., adsl, by = c("USUBJID"))

ex$AVALCAT1 <- droplevels(ex$AVALCAT1)
ex$AVALCAT1 <- factor(ex$AVALCAT1, levels = catlevels)

colspan_trt_map <- create_colspan_map(
  adsl,
  non_active_grp = "Placebo",
  non_active_grp_span_lbl = " ",
  active_grp_span_lbl = "Active Study Agent",
  colspan_var = "colspan_trt",
  trt_var = trtvar
)

# Define layout and build table:

lyt <- rtables::basic_table(
  top_level_section_div = " ",
  show_colcounts = TRUE,
  colcount_format = "N=xx"
) %>%
  split_cols_by(
    "colspan_trt",
    split_fun = trim_levels_to_map(map = colspan_trt_map)
  )

if (combined_colspan_trt == TRUE) {
  lyt <- lyt %>%
    split_cols_by(trtvar, split_fun = mysplit)
} else {
  lyt <- lyt %>%
    split_cols_by(trtvar)
}

lyt <- lyt %>%
  analyze(
    "STUDYID",
    var_labels = "Compliance (%)~[super a]",
    afun = a_freq_j,
    extra_args = list(label = "N", .stats = "n_df"),
    indent_mod = 0L,
    show_labels = "visible"
  ) %>%
  analyze("AVAL", show_labels = "hidden", indent_mod = 2L, afun = function(x) {
    list(
      "Mean (SD)" = rcell(
        c(mean(x), sd(x)),
        format = jjcsformat_xx("xx.x (xx.xx)")
      ),
      "Median" = rcell(median(x), format = jjcsformat_xx("xx.x")),
      "Min, max" = rcell(c(min(x), max(x)), format = jjcsformat_xx("xx., xx."))
    )
  }) %>%
  analyze(
    "AVALCAT1",
    nested = FALSE,
    var_labels = "Compliance ~[super a], n (%)", #TODO: FIX THIS
    afun = a_freq_j,
    extra_args = list(
      denom = "n_df",
      .stats = c("count_unique_fraction")
    ),
    indent_mod = 1L,
    show_labels = "visible"
  ) %>%
  append_topleft("Parameter")

result <- build_table(lyt, ex, alt_counts_df = adsl)

# Add titles and footnotes:

result <- set_titles(result, tab_titles)

# Convert to tbl file and output table

tt_to_tlgrtf(string_map = string_map, tt = result, file = fileid, orientation = "portrait")

TSIEX10: Study Treatment Compliance; Safety Analysis Set (Study jjcs - core)
	Active Study Agent
	Xanomeline High Dose	Xanomeline Low Dose	Combined	Placebo
Parameter	N=53	N=73	N=126	N=59
Compliance (%)a
N	53	73	126	59
Mean (SD)	63.7 (35.23)	66.5 (38.42)	65.3 (36.99)	57.0 (36.23)
Median	64.0	70.0	68.0	50.0
Min, max	0, 120	1, 122	0, 122	1, 124

Compliance a, n (%)
<60%	22 (41.5%)	28 (38.4%)	50 (39.7%)	32 (54.2%)
60% to <80%	11 (20.8%)	13 (17.8%)	24 (19.0%)	9 (15.3%)
80% to <100%	8 (15.1%)	14 (19.2%)	22 (17.5%)	8 (13.6%)
≥100%	12 (22.6%)	18 (24.7%)	30 (23.8%)	10 (16.9%)

a Compliance is calculated as (actual number of [tablets taken]/total number of [tablets supposed to be taken]) x100 / number of days taking study treatment/total treatment duration[(including days off study treatment) }x100 / (amount dispensed-amount returned)/amount dispensed x100].

Download RTF file

--- title: TSIEX10 subtitle: Study Treatment Compliance --- ------------------------------------------------------------------------ {{< include ../../_utils/envir_hook.qmd >}} ```{r setup, echo = FALSE, warning = FALSE, message = FALSE} options(docx.add_datetime = FALSE, tidytlg.add_datetime = FALSE) envsetup_config_name <- "default" # Path to the combined config file envsetup_file_path <- file.path("../..", "envsetup.yml") Sys.setenv(ENVSETUP_ENVIRON = '') library(envsetup) loaded_config <- config::get(config = envsetup_config_name, file = envsetup_file_path) envsetup::rprofile(loaded_config) dpscomp <- compound dpspdr <- paste(protocol,dbrelease,rpteff,sep="__") aptcomp <- compound aptpdr <- paste(protocol,dbrelease,rpteff,sep="__") ###### Study specific updates (formerly in envre) dpscomp <- "standards" dpspdr <- "jjcs__NULL__jjcs - core" apt <- FALSE library(junco) default_str_map <- rbind(default_str_map, c("&ctcae", "5.0")) ``` ## Output :::: panel-tabset ## {{< fa regular file-lines sm fw >}} Preview ```{r variant1, results='hide', warning = FALSE, message = FALSE} # Program Name: tsiex10.R # Prep Environment library(envsetup) library(tern) library(dplyr) library(rtables) library(junco) # Define script level parameters: # - Define output ID and file location tblid <- "TSIEX10" fileid <- tblid tab_titles <- get_titles_from_file(input_path = '../../_data/', tblid) string_map <- default_str_map trtvar <- "TRT01A" popfl <- "SAFFL" catlevels <- c("<60%", "60% to <80%", "80% to <100%", ">=100%") combined_colspan_trt <- TRUE if (combined_colspan_trt == TRUE) { # Set up levels and label for the required combined columns add_combo <- add_combo_facet( "Combined", label = "Combined", levels = c("Xanomeline High Dose", "Xanomeline Low Dose") ) # choose if any facets need to be removed - e.g remove the combined column for placebo rm_combo_from_placebo <- cond_rm_facets( facets = "Combined", ancestor_pos = NA, value = " ", split = "colspan_trt" ) mysplit <- make_split_fun(post = list(add_combo, rm_combo_from_placebo)) } # Process Data: # Read in required data adsl <- pharmaverseadamjnj::adsl %>% filter(!!rlang::sym(popfl) == "Y") %>% select(STUDYID, USUBJID, all_of(trtvar), all_of(popfl)) # If AVISIT is not present in ADEXSUM than create 'Overall' as the Visit, which is used # for the filtering AVISIT records if it does exist adexsum <- pharmaverseadamjnj::adexsum %>% mutate(VISIT = if (exists("AVISIT")) AVISIT else "Overall") %>% filter(PARAMCD == "TRTCOMP" & !is.na(AVAL) & VISIT == "Overall") %>% select(USUBJID, PARAMCD, AVAL, AVALCAT1) adsl$colspan_trt <- factor( ifelse(adsl[[trtvar]] == "Placebo", " ", "Active Study Agent"), levels = c("Active Study Agent", " ") ) # join data together ex <- adexsum %>% inner_join(., adsl, by = c("USUBJID")) ex$AVALCAT1 <- droplevels(ex$AVALCAT1) ex$AVALCAT1 <- factor(ex$AVALCAT1, levels = catlevels) colspan_trt_map <- create_colspan_map( adsl, non_active_grp = "Placebo", non_active_grp_span_lbl = " ", active_grp_span_lbl = "Active Study Agent", colspan_var = "colspan_trt", trt_var = trtvar ) # Define layout and build table: lyt <- rtables::basic_table( top_level_section_div = " ", show_colcounts = TRUE, colcount_format = "N=xx" ) %>% split_cols_by( "colspan_trt", split_fun = trim_levels_to_map(map = colspan_trt_map) ) if (combined_colspan_trt == TRUE) { lyt <- lyt %>% split_cols_by(trtvar, split_fun = mysplit) } else { lyt <- lyt %>% split_cols_by(trtvar) } lyt <- lyt %>% analyze( "STUDYID", var_labels = "Compliance (%)~[super a]", afun = a_freq_j, extra_args = list(label = "N", .stats = "n_df"), indent_mod = 0L, show_labels = "visible" ) %>% analyze("AVAL", show_labels = "hidden", indent_mod = 2L, afun = function(x) { list( "Mean (SD)" = rcell( c(mean(x), sd(x)), format = jjcsformat_xx("xx.x (xx.xx)") ), "Median" = rcell(median(x), format = jjcsformat_xx("xx.x")), "Min, max" = rcell(c(min(x), max(x)), format = jjcsformat_xx("xx., xx.")) ) }) %>% analyze( "AVALCAT1", nested = FALSE, var_labels = "Compliance ~[super a], n (%)", #TODO: FIX THIS afun = a_freq_j, extra_args = list( denom = "n_df", .stats = c("count_unique_fraction") ), indent_mod = 1L, show_labels = "visible" ) %>% append_topleft("Parameter") result <- build_table(lyt, ex, alt_counts_df = adsl) # Add titles and footnotes: result <- set_titles(result, tab_titles) # Convert to tbl file and output table tt_to_tlgrtf(string_map = string_map, tt = result, file = fileid, orientation = "portrait") ``` ```{r result1, echo=FALSE, message=FALSE, warning=FALSE, test = list(result_v1 = "result")} tt_to_flextable_j(result, tblid, string_map = string_map) ``` [Download RTF file](`r paste0(tolower(tblid), '.rtf')`) ::::